DBMS > Apache Drill vs. ClickHouse vs. SAP IQ

System Properties Comparison Apache Drill vs. ClickHouse vs. SAP IQ

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Columnar RDBMS optimized for Big Data analytics

Primary database model

Document store
Relational DBMS

Relational DBMS

column-oriented

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.89
Rank	#122	Overall
	#22	Document stores
	#58	Relational DBMS

Score	18.77
Rank	#31	Overall
	#19	Relational DBMS

Score	2.35
Rank	#103	Overall
	#52	Relational DBMS

Website

drill.apache.org

clickhouse.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

drill.apache.org/docs

clickhouse.com/docs

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

Clickhouse Inc.

SAP, formerly Sybase

Initial release

2012

2016

1994

Current release

1.20.3, January 2023

v24.6.2.17-stable, July 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C++

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

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Recent citations in the news

Apache Drill vs. Apache Spark – Which SQL query engine is better for you?
23 September 2019, Towards Data Science

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, theserverside.com

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, Business Wire

MapR Bolsters Hadoop Distro with Apache Drill for SQL-Based Big Data Analytics
22 May 2015, Visual Studio Magazine

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